48 research outputs found
Bringing the margin to the focus: 10 challenges for riparian vegetation science and management
Riparian zones are the paragon of transitional ecosystems, providing critical habitat and ecosystem services that are especially threatened by global change. Following consultation with experts, 10 key challenges were identified to be addressed for riparian vegetation science and management improvement: (1) Create a distinct scientific community by establishing stronger bridges between disciplines; (2) Make riparian vegetation more visible and appreciated in society and policies; (3) Improve knowledge regarding biodiversityâecosystem functioning links; (4) Manage spatial scale and context-based issues; (5) Improve knowledge on social dimensions of riparian vegetation; (6) Anticipate responses to emergent issues and future trajectories; (7) Enhance tools to quantify and prioritize ecosystem services; (8) Improve numerical modeling and simulation tools; (9) Calibrate methods and increase data availability for better indicators and monitoring practices and transferability; and (10) Undertake scientific validation of best management practices. These challenges are discussed and critiqued here, to guide future research into riparian vegetation
Monitoring dam removal impacts on riparian vegetation unsing very high spatial and temporal resolution remote sensing
Les cours dâeau font lâobjet de prescriptions lĂ©gislatives encourageant leur restauration, et lâarasement de barrages est une des solutions utilisĂ©es actuellement en France pour y parvenir. La vĂ©gĂ©tation riparienne participe Ă lâintĂ©gritĂ© et Ă la stabilitĂ© des systĂšmes fluviaux, Elle est donc une composante majeure Ă Ă©valuer dans le cadre des actions de restauration .Les objectifs de la thĂšse sont d'analyser la dynamique de colonisation des berges exondĂ©es Ă court terme dans le contexte de lâarasement des barrages de la SĂ©lune (Normandie) et de dĂ©velopper des indicateurs de suivi Ă long terme des zones ripariennes. Dans un premier temps, une analyse des dynamiques de colonisation aux Ă©chelles intra et interannuelles rĂ©alisĂ©e Ă lâaide dâimages drone et de relevĂ©s terrain a rĂ©vĂ©lĂ© la pertinence de lâutilisation dâimages drones pour cartographier la vĂ©gĂ©tation, ainsi que des dynamiques successionnelles rapides, avec un potentiel de restauration passive et de stabilisation des sĂ©diments. Dans un second temps, lâanalyse de nuages de points LiDAR en trois dimensions acquis en hiver et en Ă©tĂ© a montrĂ© la complĂ©mentaritĂ© des deux dates dâacquisition pour cartographier des indicateurs de statut des ripisylves Ă large Ă©chelle tels que les essences principales, lâombrage ou la densitĂ© de strates herbacĂ©es et arbustives. Ces rĂ©sultats permettent de discuter les dimensions mĂ©thodologiques et opĂ©rationnelles de lâutilisation des approches par tĂ©lĂ©dĂ©tection pour le suivi des ripisylves.Rivers are the object of legislation encouraging their restoration, and dam removal operations represent one of the solution to achieve it in France. Riparian vegetation plays a fundamental role in stabilizing and maintaining fluvial systems, being at the interface between terrestrial and aquatic environments. It is therefore a very important component which has to be evaluated in river restoration operations. One of the consequences of dam removal on riparian vegetation is the colonization of the dewatered sediments in the reservoir. The objective of the thesis are to define short term colonization dynamics of vegetation in context of dam removal (SĂ©lune River, Normandy), and to develop long term indicators for the monitoring of riparian vegetation. First, an analysis of intra and interannual colonization dynamics revealed the potential of using drone images to map riparian vegetation, and fast successional dynamics with high passive restoration and sediment stabilization potential. Secondly, the analysis of 3D point clouds extracted from LiDAR data acquired in winter and summer highlighted the complementarity of the two acquisition dates to map indicators of riparian status at large scale, such as main riparian species, shading or density of herbaceous and shrubby strata. These results make it possible to discuss the methodological and operational dimensions of the use of remote sensing approaches for the monitoring of riparian vegetatio
Suivi des impacts dâun arasement de barrage sur la vĂ©gĂ©tation riveraine par tĂ©lĂ©dĂ©tection Ă trĂšs haute rĂ©solution spatiale et temporelle
Rivers are the object of legislation encouraging their restoration, and dam removal operations represent one of the solution to achieve it in France. Riparian vegetation plays a fundamental role in stabilizing and maintaining fluvial systems, being at the interface between terrestrial and aquatic environments. It is therefore a very important component which has to be evaluated in river restoration operations. One of the consequences of dam removal on riparian vegetation is the colonization of the dewatered sediments in the reservoir. The objective of the thesis are to define short term colonization dynamics of vegetation in context of dam removal (SĂ©lune River, Normandy), and to develop long term indicators for the monitoring of riparian vegetation. First, an analysis of intra and interannual colonization dynamics revealed the potential of using drone images to map riparian vegetation, and fast successional dynamics with high passive restoration and sediment stabilization potential. Secondly, the analysis of 3D point clouds extracted from LiDAR data acquired in winter and summer highlighted the complementarity of the two acquisition dates to map indicators of riparian status at large scale, such as main riparian species, shading or density of herbaceous and shrubby strata. These results make it possible to discuss the methodological and operational dimensions of the use of remote sensing approaches for the monitoring of riparian vegetationLes cours dâeau font lâobjet de prescriptions lĂ©gislatives encourageant leur restauration, et lâarasement de barrages est une des solutions utilisĂ©es actuellement en France pour y parvenir. La vĂ©gĂ©tation riparienne participe Ă lâintĂ©gritĂ© et Ă la stabilitĂ© des systĂšmes fluviaux, Elle est donc une composante majeure Ă Ă©valuer dans le cadre des actions de restauration .Les objectifs de la thĂšse sont d'analyser la dynamique de colonisation des berges exondĂ©es Ă court terme dans le contexte de lâarasement des barrages de la SĂ©lune (Normandie) et de dĂ©velopper des indicateurs de suivi Ă long terme des zones ripariennes. Dans un premier temps, une analyse des dynamiques de colonisation aux Ă©chelles intra et interannuelles rĂ©alisĂ©e Ă lâaide dâimages drone et de relevĂ©s terrain a rĂ©vĂ©lĂ© la pertinence de lâutilisation dâimages drones pour cartographier la vĂ©gĂ©tation, ainsi que des dynamiques successionnelles rapides, avec un potentiel de restauration passive et de stabilisation des sĂ©diments. Dans un second temps, lâanalyse de nuages de points LiDAR en trois dimensions acquis en hiver et en Ă©tĂ© a montrĂ© la complĂ©mentaritĂ© des deux dates dâacquisition pour cartographier des indicateurs de statut des ripisylves Ă large Ă©chelle tels que les essences principales, lâombrage ou la densitĂ© de strates herbacĂ©es et arbustives. Ces rĂ©sultats permettent de discuter les dimensions mĂ©thodologiques et opĂ©rationnelles de lâutilisation des approches par tĂ©lĂ©dĂ©tection pour le suivi des ripisylves
Automatic extraction of former WWI battlefields from ancient maps
International audienceThe former battlefields of World War I (WWI) provide an interesting framework for studying the long-term impacts of ancient anthropogenic disturbances on current ecosystem functioning. The 47 map sheets of devastated regions at 1:50,000 scale edited in 1920 by the geographic service of French army locate the areas heavily damaged by trenches and bombing, the destructed cities, roads and forests inventoried at the end of WWI. As they stand, these scanned maps are not usable under a geographic information system (GIS). A protocol was implemented on 5 sheets to compare the effect of two transformation models (thin plate spline and polynomial order 3) and the number of ground control points on the quality of georeferencing. A second protocol based on morphological operators, color space transformation and K-means clustering classification was tested on 12 different map sheets to extract areas heavily damaged and figures of punctual destructions. Neither significant effects of transformation model or number of ground control points were confirmed. The local thin plate spline method exacerbates non-natural local distortions linked to the research of ground control points and the simplification of physical objects on the maps. With polynomial order 3 transformation and 50 ground control points, residuals vary from 35 to 70 m depending on the map. The second protocol extracted accurately data of interest, with an accuracy varying between 0.31 and 100% depending on data to extract and their presence or absence on the map sheets. The resulting shapefiles are now available and workable in GIS
Mapping Riparian Vegetation Functions Using 3D Bispectral LiDAR Data
International audienc
Tracing the scientific trajectory of riparian vegetation studies: Main topics, approaches and needs in a globally changing world
International audienc
Comparison of leaf-on and leaf-off ALS data for mapping riparian tree species
International audienc
Monitoring the colonization of alluvial deposits using multitemporal UAV RGB âimagery
International audienc
Monitoring of artificial water reservoirs in the Southern Brazilian Amazon with remote sensing data
International audienceThe agricultural expansion in the Southern Brazilian Amazon has long been pointed out due to its severe impacts on tropical forests. But the last decade has been marked by a rapid agricultural transition which enabled to reduce pressure on forests through (i) the adoption of intensive agricultural practices and (ii) the diversification of activities. However, we suggest that this new agricultural model implies new pressures on environment and especially on water resources since many artificial water reservoirs have been built to ensure crop irrigation, generate energy, farm fishes, enable access to water for cattle or just for leisure. In this paper, we implemented a method to automatically map artificial water reservoirs based on time series of Landsat images. The method was tested in the county of Sorriso (State of Mato Grosso, Brazil) where we identified 521 water reservoirs by visual inspection on very high resolution images. 68 Landsat-8 images covering 4 scenes in 2015 were pre-classified and a final class (Terrestrial or Aquatic) was determined for each pixel based on a Dempster-Shafer fusion approach. Results confirmed the potential of the methodology to automatically and efficiently detect water reservoirs in the study area (overall accuracy = 0.952 and Kappa index = 0.904) although the methodology underestimates the total area in water bodies because of the spatial resolution of Landsat images. In the case of Sorriso, we mapped 19.4 km 2 of the 20.8 km 2 of water reservoirs initially delimited by visual interpretation, i.e. we underestimated the area by 5.9%
Socio-ecological approach of agricultural practices modification in riparian areas, the example of Brittany, France
International audienc